Electronic data transfers often fall victim to fraud due to identity theft, data breaches, or otherwise insecure systems. Current methods of fraud detection depend on simple models and rules to identify potentially fraudulent electronic transactions. For example, such conventional methods may rely on whether a physical token associated with electronic data is physically present at a certain geographic transaction, a history of fraudulent electronic transactions associated with certain electronic data, or a classification associated with insecure electronic data transfers. But these simple models are imperfect, often missing actual fraud while flagging innocuous electronic transactions as fraudulent. Fraudulent electronic transactions often result in insecure data management and transfer systems as well as decreased computer system performance due to excess processing load due to the fraudulent electronic transactions, and additional corrective actions taken to remedy the fraud.
Accordingly, improved systems are needed for identifying fraudulent electronic data transactions and controlling the authorization of such electronic transactions, to reduce computer system loads, improve system efficiency, and enhance electronic data security.